Skip to main content
SpringerLink
Log in

Meta-learning Experiences with the Mindful System

  • Conference paper
Computational Intelligence and Security (CIS 2005)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 3801))

Included in the following conference series:

Abstract

In this paper, we present an original meta-learning framework, namely the Mindful (Meta INDuctive neuro-FUzzy Learning) system. Mindful is based on a neuro-fuzzy learning strategy providing for the inductive processes applicable both to ordinary base-level tasks and to more general cross-task applications. The results of an ensemble of experimental sessions are detailed, proving the appropriateness of the system in managing meta-level contexts of learning.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 129.00
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 169.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Wolpert, D.H., Macready, W.G.: No free lunch theorems for optimization. IEEE Transactions on Evolutionary Computation 1(1), 67–82 (1997)

    Article  Google Scholar 

  2. Thrun, S., Pratt, L. (eds.): Learning to Learn. Kluwer Academic Publisher, Dordrecht (1998)

    MATH  Google Scholar 

  3. Vilalta, R., Drissi, Y.: A perspective view and survey of meta-learning. Artificial Intelligence Review 18, 77–95 (2002)

    Article  Google Scholar 

  4. Giraud-Carrier, C., Vilalta, R., Brazdil, P.: Introduction to the special issue on meta-learning. Machine learning 54, 187–193 (2004)

    Article  Google Scholar 

  5. Kalousis, A., Hilario, M.: Model selection via meta-learning: a comparative study. In: Proc. of the 12th Int. IEEE Conference on Tools with AI (2000)

    Google Scholar 

  6. Ortega, J., Koppel, M., Argamon, S.: Arbitrating among competing classifiers using learned referees. Knowledge and Information Systems 3, 470–490 (2001)

    Article  MATH  Google Scholar 

  7. Soares, C., Brazdil, P., Kuba, P.: A meta-learning approach to select the kernel width in support vector regression. Machine learning 54, 195–209 (2004)

    Article  MATH  Google Scholar 

  8. Castellano, G., Castiello, C., Fanelli, A.M., Mencar, C.: Knowledge discovery by a neuro-fuzzy modeling framework. Fuzzy Sets and Systems 149, 187–207 (2005)

    Article  MATH  MathSciNet  Google Scholar 

  9. Castiello, C.: Meta-Learning: a Concern for Epistemology and Computational Intelligence. PhD Thesis. University of Bari - Italy (2004)

    Google Scholar 

  10. Michie, D., Spiegelhalter, D.J., Taylor, C.: Machine learning, neural and statistical classification. Ellis Horwood Series in Artificial Intelligence (1994)

    Google Scholar 

  11. Castiello, C., Castellano, G., Fanelli, A.M.: Meta-data: characterization of input features for meta-learning. In: Torra, V., Narukawa, Y., Miyamoto, S. (eds.) MDAI 2005. LNCS (LNAI), vol. 3558, pp. 457–468. Springer, Heidelberg (2005)

    Chapter  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. CILab – Computational Intelligence Laboratory, Dipartimento di Informatica, Università degli Studi di Bari, Via E. Orabona, 4, 70126, Bari, Italy

    Ciro Castiello & Anna Maria Fanelli

Authors
  1. Ciro Castiello
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Anna Maria Fanelli
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. Microelectronic Instiute, Xidian University, 710071, Xi’an, China

    Yue Hao

  2. Department of Computer Science, Hong Kong Baptist University, Kowloon Tong, Hong Kong

    Jiming Liu

  3. School of Computer Science and Technology, Xidian University, Xi’an, China

    Yuping Wang

  4. Department of Computer Science, Hong Kong Baptist University, Hong Kong,  

    Yiu-ming Cheung

  5. School of Electrical and Electronic Engineering, University of Manchester, UK

    Hujun Yin

  6. Life Science Research Center, School of Electronic Engineering, Xidian University, 710071, Xi’an, Shaanxi, China

    Licheng Jiao

  7. Key Laboratory of Computer Networks and Information Security (Ministry of Education), Xidian University, 710071, Xi’an, China

    Jianfeng Ma

  8. National Laboratory of Antennas and Microwave Technology, Xidian University, 710071, Xi’an, Shanxi, P.R. China

    Yong-Chang Jiao

Rights and permissions

Reprints and permissions

Copyright information

© 2005 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Castiello, C., Fanelli, A.M. (2005). Meta-learning Experiences with the Mindful System. In: Hao, Y., et al. Computational Intelligence and Security. CIS 2005. Lecture Notes in Computer Science(), vol 3801. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11596448_46

Download citation

  • DOI: https://doi.org/10.1007/11596448_46

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-30818-8

  • Online ISBN: 978-3-540-31599-5

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation